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ProbNNd shapes for charged tracks from MC. Deuterons are taken from a 2016 Yields of each track type is normalised to unity. |
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Profile histogram of ProbNNd in bins of momentum for MC tracks in range 0 < p < 100 GeV.c. MC samples are the same as above. Features in the shapes can be attributed to the RICH thresholds, where separation between the particles changes. 9.3 GeV/c is RICH 1 kaon threshold 15.3 GeV/c is RICH 2 kaon threshold 17.7 GeV/c is RICH 1 proton threshold 29.7 GeV/c is RICH 2 proton threshold 35.4 GeV/c is RICH 1 deuteron threshold 59.3 GeV/c is RICH 2 deuteron threshold |
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A template fit to a toy histogram in ProbNNd, with shapes for each component taken from MC (deuterons from 2016 This is for the momentum region 29.7 < p < 35.4 GeV/c, with the relative yields of each of the track types taken from generator-level MC of prompt deuteron production. Integrated number of entries in the plot approximately matches the number of tracks in the NoBias 2017 data sample for this momentum bin. Note the variable width bins on the x-axis, which are plotted evenly; the binning was chosen such that the deuteron shape would be flat, so the plot is concentrated in the very high ProbNNd region. |
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The expected deuteron yield as a ratio of pion yield, in bins of momentum, using two deuteron production models: coalesence and cross-section. The These yields were taken from generator-level MC. Gauss is used to generate the Approved on 18/09/2018: https://indico.cern.ch/event/757547/contributions/3144861/attachments/1717660/2771699/Plot_approval.pdf |
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Plot to demonstrate the separation offered by DLL variables. Normalised pion and deuteron distributions in DLL Approved on 18/09/2018: https://indico.cern.ch/event/757547/contributions/3144861/attachments/1717660/2771699/Plot_approval.pdf |
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In bins of momentum, deuteron-selection efficiencies for deuterons, and mis-ID efficiencies for For deuterons, the efficiencies are taken from a MC sample ( Approved on 18/09/2018: https://indico.cern.ch/event/757547/contributions/3144861/attachments/1717660/2771699/Plot_approval.pdf |
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In bins of momentum, deuteron-selection efficiencies for deuterons, and mis-ID efficiencies for For deuterons, the efficiencies are taken from a MC sample ( Approved on 18/09/2018: https://indico.cern.ch/event/757547/contributions/3144861/attachments/1717660/2771699/Plot_approval.pdf |
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Kaon identification efficiency and pion misidentification rate as measured using 2017 MagDown data as a function of track momentum. Two different \DeltaLLKPi requirements have been imposed on the samples, resulting in the open and filled marker distributions, respectively. |
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Proton identification efficiency and pion misidentification rate as measured using 2017 MagDown data as a function of track momentum. Two different \DeltaLLPPi requirements have been imposed on the samples, resulting in the open and filled marker distributions, respectively. |
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Proton identification efficiency and kaon misidentification rate as measured using 2017 MagDown data as a function of track momentum. Two different \DeltaLLPK requirements have been imposed on the samples, resulting in the open and filled marker distributions, respectively. |
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Muon identification efficiency and pion misidentification rate as measured using 2017 MagDown data as a function of track momentum. Two different identification requirements have been imposed on the samples, resulting in the open (isMuon) and filled marker distributions (\DeltaLLMuPi), respectively. |
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Muon identification efficiency and kaon misidentification rate as measured using 2017 MagDown data as a function of track momentum. Two different identification requirements have been imposed on the samples, resulting in the open (isMuon) and filled marker distributions (\DeltaLLMuK), respectively. |
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Muon identification efficiency and proton misidentification rate as measured using 2017 MagDown data as a function of track momentum. Two different identification requirements have been imposed on the samples, resulting in the open (isMuon) and filled marker distributions (\DeltaLLMuP), respectively. |
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Kaon identification efficiency and pion misidentification rate as measured using 2016 MagDown data as a function of track momentum. Two different \DeltaLLKPi requirements have been imposed on the samples, resulting in the open and filled marker distributions, respectively. |
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Kaon identification efficiency and pion misidentification rate as measured using 2016 MagUp data as a function of track momentum. Two different \DeltaLLKPi requirements have been imposed on the samples, resulting in the open and filled marker distributions, respectively. |
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Kaon identification efficiency and pion misidentification rate as measured using 2016 data (MagDown + MagUp) as a function of track momentum. Two different \DeltaLLKPi requirements have been imposed on the samples, resulting in the open and filled marker distributions, respectively. |
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Kaon identification efficiency and pion misidentification rate as measured using 2016 data with different \DeltaLLKPi requirements. |
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Muon identification efficiency and pion misidentification rate as measured using 2017 MagDown data as a function of track momentum. Two different identification requirements have been imposed on the samples, resulting in the open (isMuon) and filled marker distributions (\DeltaLLMuPi), respectively. |
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Muon identification efficiency and kaon misidentification rate as measured using 2017 MagDown data as a function of track momentum. Two different identification requirements have been imposed on the samples, resulting in the open (isMuon) and filled marker distributions (\DeltaLLMuK), respectively. |
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Muon identification efficiency and proton misidentification rate as measured using 2017 MagDown data as a function of track momentum. Two different identification requirements have been imposed on the samples, resulting in the open (isMuon) and filled marker distributions (\DeltaLLMuP), respectively. |
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Kaon identification efficiency and pion misidentification rate as measured using 2015 data as a function of track momentum. Two different \DeltaLLKPi requirements have been imposed on the samples, resulting in the open and filled marker distributions, respectively. |
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Proton identification efficiency and kaon misidentification rate as measured using 2015 data as a function of track momentum. Two different \DeltaLLPK requirements have been imposed on the samples, resulting in the open and filled marker distributions, respectively. |
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Proton identification efficiency and pion misidentification rate as measured using 2015 data as a function of track momentum. Two different \DeltaLLPPi requirements have been imposed on the samples, resulting in the open and filled marker distributions, respectively. |
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Kaon identification efficiency and pion misidentification rate as measured using 2012 data as a function of track momentum. Two different \DeltaLLKPi requirements have been imposed on the samples, resulting in the open and filled marker distributions, respectively. |
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Proton identification efficiency and kaon misidentification rate as measured using 2012 data as a function of track momentum. Two different \DeltaLLPK requirements have been imposed on the samples, resulting in the open and filled marker distributions, respectively. |
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Proton identification efficiency and pion misidentification rate as measured using 2012 data as a function of track momentum. Two different \DeltaLLPPi requirements have been imposed on the samples, resulting in the open and filled marker distributions, respectively. |
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Reconstructed Cherenkov angle for \emph{isolated} tracks, as a function of track momentum in the \cfourften radiator. The Cherenkov bands for muons, pions, kaons and protons are clearly visible. |
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Kaon identification efficiency and pion misidentification rate as measured using data as a function of track momentum. Two different \DeltaLLKPi requirements have been imposed on the samples, resulting in the open and filled marker distributions, respectively. |
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Kaon identification efficiency and pion misidentification rate from simulation as a function of track momentum. Two different \DeltaLLKPi requirements have been imposed on the samples, resulting in the open and filled marker distributions, respectively. |
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Pion misidentification fraction versus kaon identification efficiency as measured in 7\,TeV LHCb collisions as a function of track multiplicity. The efficiencies are averaged over all particle momenta. |
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Pion misidentification fraction versus kaon identification efficiency as measured in 7\,TeV LHCb collisions as a function of the number of reconstructed primary vertices. The efficiencies are averaged over all particle momenta. |
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Electron identification performance using the $\deltaLLCombepi$ variable, as measured in 8\,TeV collision data, using a tag and probe technique with electrons from the decay $B^{\pm} \to (J/\psi \to e^+e^-) K^{\pm}$. Pion misidentication rate versus electron identification probability when the cut value is varied. |
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Electron identification performance using the $\deltaLLCombepi$ variable, as measured in 8\,TeV collision data, using a tag and probe technique with electrons from the decay $B^{\pm} \to (J/\psi \to e^+e^-) K^{\pm}$. Electron identification efficiency and pion misidentification rate as a function of track momentum, for two different cuts on $\deltaLLCombepi$. |
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Background misidentification rates versus muon identification efficiency, as measured in the $\Sigma^+\to p\mu^+\mu^-$ decay study. The variables $\deltaLLXpi$ (black) and ProbNN (red), the probability value for each particle hypothesis, are compared for $5-10$\gevc muons and $5-50$\gevc protons, using data sidebands for backgrounds and Monte Carlo simulation for the signal. |
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Background misidentification rates versus proton identification efficiency, as measured in the $\Sigma^+\to p\mu^+\mu^-$ decay study. The variables $\deltaLLXpi$ (black) and ProbNN (red), the probability value for each particle hypothesis, are compared for $5-10$\gevc muons and $5-50$\gevc protons, using data sidebands for backgrounds and Monte Carlo simulation for the signal. |